The present invention relates to the field of wireless mobile devices and software applications installed thereon. More particularly, the present invention relates to predicting performance of such devices and software applications.
According to a study by Flurry individuals in the United States used mobile applications for 127 minutes a day during the month of December 2012, which was 35% more than a year earlier. Nonetheless when mobile application developers develop a new application or a new version of an application there are limited tools for predicting the performance before an application is released to a wide audience.
There are tools available, like Apple's Instruments, which provide performance information in a controlled development environment. Such tools do not anticipate the various environments that the application might run in, such as limited cellular networks, handsets with limited memory, or operating system versions with features limiting performance. A partial solution then is to use a mobile testing solution, like the one from Keynote Systems, which provide a panel of testers with mobile devices to test performance. The limitation of these solutions is that they use a sample of the total population of mobile users; therefore they cannot do an exhaustive job of providing performance for the thousands of configurations among end users including varying geographies, network connections, mobile devices, mobile application characteristics, and operating system versions. Also for a given configuration these solutions have data that is limited by the size of the panel.
Thus there is a need for a solution that predicts the performance of mobile applications for an exhaustive list of possible end user conditions and application characteristics. Also there is a need for a solution that leverages more than just the limited data provided by a sample panel to predict mobile application performance.